Biomechanically constrained groupwise statistical shape model to ultrasound registration of the lumbar spine

Authors:
Siavash Khallaghi;Parvin Mousavi;Dan Borschneck;Gabor Fichtinger;Purang Abolmaesumi
Affiliations:
University of British Columbia, Vancouver, BC, Canada;Queen's University, Kingston, ON, Canada;Queen's University, Kingston, ON, Canada;Queen's University, Kingston, ON, Canada;University of British Columbia, Vancouver, BC, Canada
Venue:
IPCAI'11 Proceedings of the Second international conference on Information processing in computer-assisted interventions
Year:
2011

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Abstract

Spinal needle injections for back pain management are frequently carried out in hospitals and radiological clinics. Currently, these procedures are performed under fluoroscopy or CT guidance in specialized interventional radiology facilities. As an alternative, the use of inexpensive ultrasound image guidance promises to reduce the costs and increase the availability and safety of procedure. We propose to eliminate the need for ionizing radiation by creating a statistical shape model of the lumbar vertebrae and registering it to 3D ultrasound volumes of patient using a groupwise registration algorithm. From a total of 35 patient CT volumes, statistical shape models of the L2, L3 and L4 vertebrae are created, including the mean shapes and principal modes of variation. The statistical shape models are simultaneously registered to the 3D ultrasound by interchangeably optimizing the model parameters and their relative poses. We also use a biomechanical model to constrain the relative motion of the individual vertebra models throughout the registration process. The proposed method was validated on three phantoms with realistic spinal curvatures.